Promoting Industry 4.0 through SW engineer career and newly learned data science

POWER SOLUTIONS
DIVISION

Junichi T.

Power Solutions Division
Manufacturing Department, Manufacturing Technology
Production Engineering
SW Engineer
Joined Bosch in 2018

Chapter 01

Changed jobs from a Japanese automobile manufacturer to continue learning at the forefront of software

When I was in high school, I became interested in automobiles and thought that the future of automobiles would be software, so I chose a major that allowed me to study software at university. After joining an electronics manufacturer as a new graduate, I was involved in the development of automotive audio, and then moved to a Japanese automobile manufacturer to be involved in cutting-edge software development. There, I was in charge of evaluating the performance of ADAS (Advanced Driver Assistance Systems).

At that time, although many companies were focusing on automated driving technology, it was difficult to work in new fields in my previous job, and I myself was required to leave the front lines and engage in management. I wanted to continue learning at the forefront of software development until I was 40. I wanted to put myself in an environment where I could write my own code, so I started looking for a new job.

I chose Bosch because I wanted to be an engineer who could not only manage cutting-edge technology, but also be involved in the field, as well as play an active role globally. Although it was my second time changing jobs, it was my first time joining a foreign-affiliated company. I was nervous at first, because I thought that the atmosphere would be more dry or detached than that of Japanese companies. However, that image was overturned when I first met with my boss. My boss kindly thought about what kind of career I could develop and my career plan, and I learned that there were a wide variety of study programs. I think that Bosch's culture emphasizes long-term human resource development more than I experienced at my previous companies. This is a difference in a good way.

Chapter 02

Acquire data science knowledge through global hands-on training and apply it to projects

The mission of my current team is to promote Industry 4.0, which is to say digital transformation (DX), at the manufacturing site. I am mainly in charge of data analysis and business improvement using AI. As a specific example, product inspection takes a lot of man-hours at manufacturing sites, so we are building an AI model that detects defects during product inspection. As a result, we have succeeded in significantly reducing the number of inspection man-hours.

Actually, I had no experience with AI before joining Bosch. I am now able to take charge of this task thanks to the "Data Scientist Training" that is part of Bosch's educational program. I had communicated my interest in AI technology with my boss, and I had the opportunity to take the training as the first participant from the Power Solutions Division.

The training was long-term and lasted nine months. It started with the acquisition of basic knowledge such as Python and SQL, lectures and group work with overseas universities, AI-related issues, and so on. The content was intense, allowing students to learn practical data science with colleagues from all over the world. I spent about 50% of my working time learning, and as a result of buying reference books almost every week and studying hard, I was able to acquire knowledge of data science. At Bosch, if you communicate what you want to do, you will be given a chance. I think this kind of environment is one of the major attractions of Bosch.

Chapter 03

As a bridge engineer, I want to solve problems at the manufacturing site with my own hands.

There are still many analog aspects at Japanese manufacturing sites, including at Bosch. That is why I find it very rewarding to be involved in the promotion of DX at manufacturing sites. While it is said that there are many challenges, Bosch has organizations that are working on cutting-edge digital technology, such as the Cross-Domain Computing Solutions Division, and there are also sites in Germany and other overseas factories that are making progress in utilizing AI. I think the fact that we can work on DX while sharing information with bases around the world is a great advantage.

I myself gained knowledge of data science through training, but in order to truly utilize AI, it is essential to collect data in the correct form. In addition, it is necessary to build a model based on an understanding of the issues at the manufacturing site. I believe that it is necessary to play the role of a "bridge engineer" who promotes DX while staying close to the manufacturing site.

My current goal is to use an AI model that I created myself to implement a business improvement system to actual equipment, so that workers will say that the work has become more convenient. After that, I would like to be in a position to coordinate DX at the manufacturing site, and create a team that makes people think, "Let's consult this department for DX at the manufacturing site." In this environment where I can deepen my studies in a crosscutting manner, I would like to continue to actively learn cutting-edge technologies and take on the challenge of putting them into practice in the field.